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Record W4404453838 · doi:10.35680/2372-0247.1918

Post-Pandemic Needs of Unpaid Family and Friend Caregivers to Effectively Continue Caregiving Duties in one Northern Ontario Health Authority

2024· article· en· W4404453838 on OpenAlexaffabout
Jodi Webber, Erin M Mulroney, Mark Tatasciore, Brianna Smith, Louis Ferron, Hannah Albani, Bianca Feitelberg, Laura Tenhagen, Sophia Myles

Bibliographic record

VenuePatient Experience Journal · 2024
Typearticle
Languageen
FieldHealth Professions
TopicGeriatric Care and Nursing Homes
Canadian institutionsCancer Care OntarioLaurentian UniversitySault Area HospitalEssar Steel Algoma (Canada)Algoma University
Fundersnot available
KeywordsPandemicFamily caregiversNursingMedicineCoronavirus disease 2019 (COVID-19)PsychologyGerontologyDisease

Abstract

fetched live from OpenAlex

The Covid-19 pandemic had a significant impact on the support networks for older adults and caregivers as health and social care systems were forced to dramatically change the ways patients and clients interacted with providers, services, and programs. In Northern Ontario, caregivers are older, caring in more intense situations, more likely to be caring for multiple care recipients simultaneously and less likely to be in contact with health professionals. This research sought to explore the post-pandemic needs of caregivers in a Northern Ontario health catchment to better understand the needed supports. Using a collaborative and co-design approach with caregiver advisors within a qualitative description design, seven focus groups were conducted with 36 participants in total in February 2023. Reflexive thematic analysis was used to generate five themes from the transcripts: caregivers as the invisible but vital backbone of health and social care; amplified distress: navigating overwhelming demands; family fault lines exposed; contextualized care: the need for personalized supports; and empowering caregivers through training and supports. Our findings suggest that the pandemic significantly impacted the already vulnerable support networks for older adults and caregivers, as health and social care systems had to adapt to new restrictions and limitations. Caregivers were forced to take on additional responsibilities and cope with social isolation, leading to detrimental effects on their mental health and overall well-being.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.047
Threshold uncertainty score0.936

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.037
GPT teacher head0.348
Teacher spread0.311 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2024
Admission routes2
Has abstractyes

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